This proposal builds upon our successes in the first funding cycle, and technological advances in in the wider scientific community. We will expand our understanding of the biology and sequence-based encryption of transcriptional regulatory instructions in clinically pertinent neuronal populations, focusing on tyrosine hydroxylase (Th)-expressing ventral midbrain neurons that are compromised in Parkinson's disease and certain behavioral and neuropsychiatric disorders. In recent years, we have made great strides in characterizing regulatory control at specific neurogenic loci by generating, validating and publicly depositing huge catalogs of neuronal enhancers. We have developed and implemented computational strategies that catalog key motif combinations that identify neuronal enhancers, and developed sequence- based vocabularies (classifiers) for neuroanatomical domains (forebrain, midbrain, hindbrain) among other more homogenous isolated cell populations. By integrating our experiences in functional and computational genomics we have been able to indict several disease-associated variants in pertinent biological processes. We are also beginning to develop the capacity to impute the functional impact of non-coding variation from primary sequence alone. Efforts to understand the architecture of human complex disease through Genome Wide Association Studies have drawn increased attention to potential roles played by regulatory variation. Thus, understanding the connections between regulatory variants and disease risk is very important. We propose detailed characterization of cell-type appropriate genome-wide regulatory sequence catalogs, isolating labeled dopaminergic neurons ex vivo at multiple time points (Aim 1). We will functionally validate the catalogs and define the sequence motifs that specify their function, developing computational classifiers to identify human DA enhancers, and assaying the functional impact of disease-associated variants therein (Aim 2). We will determine the relationship between distal-acting regulatory sequences and their cognate genes using cutting edge chromatin conformation capture (3C)-based strategies to reveal enhancers- promoter interactions. Then we will determine the consequences of deleting selected enhancers using contemporary genome editing strategies (Aim 3). This proposal takes crucial next steps towards a neuronal regulatory lexicon that can inform our observation of disease-associated variation in non-coding, putative regulatory sequence space.